The advent of robotic bronchoscopy coupled with electromagnetic navigation bronchoscopy (EMN) and shape-sensing technology have increased diagnostic yields for peripheral pulmonary nodules compared to traditional bronchoscopy. Yet, diagnostic yields from these bronchoscopic platforms still fall short of where they should be. This shortfall is in large part due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD). Digital lung tomosynthesis (DLT) is an advanced imaging modality that helps overcome CTBD during bronchoscopic biopsies of lung nodules. DLT is a quasi-3D imaging technique, which reconstructs tomographic images of the lung from a series of 2D fluoroscopic projection images. These images can be acquired either using a digital flat panel fluoroscopy machine or a fluoroscopy machine with a more traditional image-intensifier present in most standard bronchoscopy suites. This review aims to explain the mechanisms of both CTBD and DLT to help diagnose early-stage lung cancer more effectively.